{"id":"https://openalex.org/W2101947982","doi":"https://doi.org/10.1109/igarss.2007.4423923","title":"Contaminant source estimation in a two-layers porous environment using a Bayesian approach","display_name":"Contaminant source estimation in a two-layers porous environment using a Bayesian approach","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2101947982","doi":"https://doi.org/10.1109/igarss.2007.4423923","mag":"2101947982"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2007.4423923","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2007.4423923","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071998338","display_name":"Aur\u00e9lien Hazart","orcid":null},"institutions":[{"id":"https://openalex.org/I102475099","display_name":"Sup\u00e9lec","ror":"https://ror.org/00n7gwn90","country_code":"FR","type":"education","lineage":["https://openalex.org/I102475099"]},{"id":"https://openalex.org/I4210143116","display_name":"\u00c9lectricit\u00e9 de France (France)","ror":"https://ror.org/03wb8xz10","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210143116"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Aurelien Hazart","raw_affiliation_strings":["L2S, Sup\u00e9lec-Plateau de Moulon, Gif-sur-Yvette, France","Electricite de France, Chatou"],"affiliations":[{"raw_affiliation_string":"L2S, Sup\u00e9lec-Plateau de Moulon, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I102475099"]},{"raw_affiliation_string":"Electricite de France, Chatou","institution_ids":["https://openalex.org/I4210143116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091811958","display_name":"Jean\u2010Fran\u00e7ois Giovannelli","orcid":"https://orcid.org/0000-0002-0372-9329"},"institutions":[{"id":"https://openalex.org/I102475099","display_name":"Sup\u00e9lec","ror":"https://ror.org/00n7gwn90","country_code":"FR","type":"education","lineage":["https://openalex.org/I102475099"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jean-Francois Giovannelli","raw_affiliation_strings":["L2S, Sup\u00e9lec-Plateau de Moulon, Gif-sur-Yvette, France","L2S (CNRS-Sup\u00e9lec-UPS), Sup\u00e9lec-Plateau de Moulon 91192, Gif-sur-Yvette Cedex, France"],"affiliations":[{"raw_affiliation_string":"L2S, Sup\u00e9lec-Plateau de Moulon, Gif-sur-Yvette, France","institution_ids":["https://openalex.org/I102475099"]},{"raw_affiliation_string":"L2S (CNRS-Sup\u00e9lec-UPS), Sup\u00e9lec-Plateau de Moulon 91192, Gif-sur-Yvette Cedex, France","institution_ids":["https://openalex.org/I102475099","https://openalex.org/I1294671590"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040886351","display_name":"St\u00e9phanie Dubost","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102085","display_name":"Laboratoire d'\u00c9lectrotechnique et d'\u00c9lectronique de Puissance de Lille","ror":"https://ror.org/0186z1m53","country_code":"FR","type":"facility","lineage":["https://openalex.org/I190752583","https://openalex.org/I190861549","https://openalex.org/I2279609970","https://openalex.org/I3132096951","https://openalex.org/I4210102085","https://openalex.org/I4210134562","https://openalex.org/I7454413"]},{"id":"https://openalex.org/I4210143116","display_name":"\u00c9lectricit\u00e9 de France (France)","ror":"https://ror.org/03wb8xz10","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210143116"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Stephanie Dubost","raw_affiliation_strings":["Electricit\u00e9 de France Research and Development, Chatou, France","Electricit\u00e9France - R&D, 6, quai Watier 78401 Chatou Cedex, France"],"affiliations":[{"raw_affiliation_string":"Electricit\u00e9 de France Research and Development, Chatou, France","institution_ids":["https://openalex.org/I4210143116"]},{"raw_affiliation_string":"Electricit\u00e9France - R&D, 6, quai Watier 78401 Chatou Cedex, France","institution_ids":["https://openalex.org/I4210102085"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024128629","display_name":"Laurence Chatellier","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102085","display_name":"Laboratoire d'\u00c9lectrotechnique et d'\u00c9lectronique de Puissance de Lille","ror":"https://ror.org/0186z1m53","country_code":"FR","type":"facility","lineage":["https://openalex.org/I190752583","https://openalex.org/I190861549","https://openalex.org/I2279609970","https://openalex.org/I3132096951","https://openalex.org/I4210102085","https://openalex.org/I4210134562","https://openalex.org/I7454413"]},{"id":"https://openalex.org/I4210143116","display_name":"\u00c9lectricit\u00e9 de France (France)","ror":"https://ror.org/03wb8xz10","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210143116"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Laurence Chatellier","raw_affiliation_strings":["Electricit\u00e9 de France Research and Development, Chatou, France","Electricit\u00e9France - R&D, 6, quai Watier 78401 Chatou Cedex, France"],"affiliations":[{"raw_affiliation_string":"Electricit\u00e9 de France Research and Development, Chatou, France","institution_ids":["https://openalex.org/I4210143116"]},{"raw_affiliation_string":"Electricit\u00e9France - R&D, 6, quai Watier 78401 Chatou Cedex, France","institution_ids":["https://openalex.org/I4210102085"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5071998338"],"corresponding_institution_ids":["https://openalex.org/I102475099","https://openalex.org/I4210143116"],"apc_list":null,"apc_paid":null,"fwci":0.34,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.65954841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4757","last_page":"4760"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10894","display_name":"Groundwater flow and contamination studies","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10894","display_name":"Groundwater flow and contamination studies","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11588","display_name":"Atmospheric and Environmental Gas Dynamics","score":0.9836999773979187,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10398","display_name":"Groundwater and Isotope Geochemistry","score":0.9814000129699707,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6716533303260803},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6238782405853271},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.5813130736351013},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.5673633813858032},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5604669451713562},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5057663917541504},{"id":"https://openalex.org/keywords/point-source","display_name":"Point source","score":0.50128173828125},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.46820002794265747},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.46626362204551697},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.43589308857917786},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.4319906234741211},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.4199385643005371},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.41462868452072144},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3843746781349182},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37672075629234314},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24160277843475342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1979946494102478},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19261837005615234}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6716533303260803},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6238782405853271},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.5813130736351013},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.5673633813858032},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5604669451713562},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5057663917541504},{"id":"https://openalex.org/C103783831","wikidata":"https://www.wikidata.org/wiki/Q2552709","display_name":"Point source","level":2,"score":0.50128173828125},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.46820002794265747},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.46626362204551697},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.43589308857917786},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.4319906234741211},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4199385643005371},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.41462868452072144},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3843746781349182},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37672075629234314},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24160277843475342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1979946494102478},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19261837005615234},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2007.4423923","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2007.4423923","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1480560153","https://openalex.org/W1985093013","https://openalex.org/W2020041557","https://openalex.org/W2030911724","https://openalex.org/W2041615844","https://openalex.org/W2049659475","https://openalex.org/W2062862681","https://openalex.org/W2069730635","https://openalex.org/W2135718845","https://openalex.org/W4292403327","https://openalex.org/W6841455387"],"related_works":["https://openalex.org/W3087071515","https://openalex.org/W71678127","https://openalex.org/W2157655363","https://openalex.org/W4205763938","https://openalex.org/W2292189132","https://openalex.org/W4288092343","https://openalex.org/W2134332527","https://openalex.org/W4386114318","https://openalex.org/W4283077537","https://openalex.org/W2999603699"],"abstract_inverted_index":{"Pollution":[0],"source":[1,26,44,72,155],"estimation":[2],"based":[3],"on":[4,24,64,74,92],"groundwater":[5],"concentration":[6],"measurements":[7],"is":[8,94,163],"an":[9],"ill-posed":[10],"inverse":[11,81],"problem":[12,39,82],"in":[13,34,102,116],"that":[14,130],"several":[15],"different":[16],"sources":[17],"can":[18],"supply":[19],"similar":[20],"observations.":[21],"Consequently,":[22],"constraints":[23],"the":[25,32,35,38,71,80,87,128,133,137,141,154],"must":[27],"be":[28],"added.":[29],"Most":[30],"of":[31,78,89,97,169],"works":[33],"literature":[36],"regularize":[37],"either":[40],"by":[41,47,157],"introducing":[42],"parametric":[43],"models":[45],"or":[46],"penalizing":[48],"undesir":[49],"able":[50],"solutions.":[51],"In":[52,59,85],"our":[53],"work,":[54],"we":[55,62],"use":[56,88],"both":[57],"strategies.":[58],"this":[60],"paper,":[61],"focus":[63],"point":[65],"and":[66,111,152],"instantaneous":[67],"pollution":[68],"source.":[69,138],"Since":[70],"depends":[73],"a":[75,95,117,124,145,166],"small":[76],"number":[77],"parameters,":[79],"becomes":[83],"over-determined.":[84],"addition,":[86],"prior":[90,112],"probability":[91,126],"parameters":[93],"way":[96],"dealing":[98],"with":[99,144],"difficult":[100],"situations":[101],"which":[103],"few":[104],"observations":[105,110],"are":[106,114],"available.":[107],"Information":[108],"from":[109],"information":[113,135],"combined":[115],"Bayesian":[118],"framework.":[119],"The":[120,160],"approach":[121],"leads":[122],"to":[123,165],"posterior":[125,142,158],"given":[127],"data":[129],"summarizes":[131],"all":[132],"available":[134],"about":[136],"We":[139],"explore":[140],"law":[143],"Markov":[146],"Chain":[147],"Monte":[148],"Carlo":[149],"sampling":[150],"method":[151,162],"estimate":[153],"characteristics":[156],"mean.":[159],"proposed":[161],"applied":[164],"simulated":[167],"case":[168],"pollution.":[170]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}